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Дискримінантний аналіз×Independent Samples t-test×Однофакторний дисперсійний аналіз×
ГалузьСтатистикаСтатистикаСтатистика
РодинаLatent structureHypothesis testHypothesis test
Рік появи193619081925
Автор методуRonald A. FisherStudent (W. S. Gosset)Ronald A. Fisher
ТипSupervised classification and dimension reductionParametric mean comparisonParametric mean comparison
Основоположне джерелоFisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗
Інші назвиLDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysisstudent t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testione-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
Пов'язані444
ПідсумокDiscriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error.The independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances.One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925.
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ScholarGateПорівняння методів: Discriminant Analysis · Independent t-test · One-way ANOVA. Отримано 2026-06-20 з https://scholargate.app/uk/compare